Introduction
As part of the CODS17 pre-conference events, 80 people participated in the Data 4 Impact Workshop on June 12th, 2017. The workshop took place between 10am – 4pm in the Edmonton Tower and was hosted by The City of Edmonton. This report back provides an overview of the workshop, a summary of the key discussions that took place during the workshop as well as a summary of the participant feedback in the post-conference survey. The results of the post-conference survey are also made available in Appendix I. The presentation itself is available here.
Overview
The objectives of the workshop were:
- To raise awareness of the value of data sharing at the organizational and sector level
- To provide frameworks that would be helpful to organizations in the development of plans to enable the effective use of data
- To increase capacity by providing techniques and tools for participants to understand how to collect and use data in their organizations and the sector
- To introduce the concept of Community Data Collaboratives
The following leaders from the nonprofit data community from across Canada were the facilitators for the workshop:
- Geoff Zakaib – Data for Good
- Jean-Noé Landry – Open North
- Nick Scott – Government of New Brunswick
- Jesse Bourns – Powered by Data
The agenda followed by the workshop was the following:
10:00 – 10:15 Introductions
10:15 – 10:45 Canadian and International Perspective
10:45 – 11:15 Alberta Perspective
11:15 – 11:30 Data Spectrum & Data Lifecycle
11:30 – 12:00 Exercise 1: Situating yourself on the data spectrum
12:00 – 01:00 Lunch
01:00 – 01:15 Report Back on Exercise 1
01:15 – 01:40 Pre-Event Questionnaire
Exercise 2:
01:40 – 02:00 Step 1: Problem Identification
02:00 – 02:30 Step 2: Solutions
02:30 – 02:45 Break
02:45 – 03:15 Step 3: Report Back
03:15 – 04:00 Plenary Sector Discussion
04:00 – 04:30 Wrap-Up, Evaluation, and Thanks!
Summary of Discussions
The following is a summary of the key discussions that took place during the workshop. Those discussions took place during the three following exercises:
- Situation Yourself on the Data Spectrum
- 5 Factors Discussion – Problem and Solution Identification
- Plenary Sector Discussion
Situating Yourself on the Data Spectrum
The Data Spectrum model created by the Open Data Institute was presented to participants. Special attention was given to provide examples of Closed, Shared, and Open data in the context of the social sector – providing the conceptual framework that was used throughout the workshop. It was important that participants understood that data sets in the social sector exist all along this continuum, and that they all have value. But in order to create even more value for the social sector, it was critical to raise awareness of the need to look for opportunities to move data from being Closed into the realm of being Shared or Open.
According to the definitions of Closed, Shared, and Open Data — participants situated examples of data sets with post-it notes on the data spectrum according to their own organization’s experience.
This was followed by a short discussion.
5 Factors Discussion – Problem and Solution Identification
For the second exercise, participants were asked to identify problems based on the 5 factors described in the presentation, and then share back to the whole group. Afterwards, participants joined groups focused on specific factors to identify potential solutions to some of those problems. The 5 factors consist of:
- Mindset
- Culture
- Infrastructure
- Social capital and sector dynamics
- Capacity
The following is a summary of the participants discussions on each of the factors:
1. Mindset
In terms of mindset, participants acknowledged the need to map out the existing mindset of folks working in nonprofits as they related to data use and sharing in their respective organizations.
Participants identified challenges to changing mindsets about data use and collection. They recognized that old organizational structures aren’t easy to change. They thought that it fairly predictable that people will say that it’s always done in certain ways as an excuse to not change them. They also recognized the fear of change, potential issues of trust, and the instinct for self-protection as other reasons people would be resistant to changing their mindset about data use and sharing.
To overcome these challenges the discussion focused on seeing mindset shifts as change management processes. It was highlighted that as part of this process it was important to be cognizant of the political, social and funding landscape. Several solutions to change mindsets about data use and sharing were also suggested:
- Getting the right leadership in place
- Focusing on the benefits of change
- Showing a willingness to listen
- Plan for increasing capacity
- Making sure to describe collective good from this work
- Targeting early adopters and demonstrating early successes
- Limiting time spent on the naysayers
- Relating the approach to existing organizational culture
- Exploring the idea of bringing in people from outside the organization
Finally, The Mindset by Carol Dweck was recommended as reading for a deeper dive on changing mindsets.
2. Culture
In terms of culture, participants saw the major challenges for creating a positive data culture were inertia as well as regularly updating data. Participants thought if data was updated quarterly, it was going to be challenging.
Participants identified these challenges were something that management/government needs to plan to tackle with policies with some teeth to them and by streamlining operations. They also thought about the importance of developing the capacity to use and share data is a key way to encourage culture. Participants believed that folks needed to be able to attend events to be educated about open data. They also thought that folks needed to see the value of what they were getting in return and understand the perceived benefits.
3. Infrastructure
As for infrastructure, participants said funding is a major hurdle. They also identified the importance of filling gaps in the data life cycle. Additionally, participants said that case studies and impact stories are hard to find. In terms of creating data collecting infrastructure, participants highlighted the need to make sure:
- what you’re collecting is relevant;
- all paper trails are digitized.
Participants also discussed increasing awareness of data collection within organizations, and the importance of creating templates, and standardizing best practices.
The idea of creating infrastructure that could be paid for on a sliding scale was discussed. Also, the fear of proprietary infrastructure was mentioned.
4. Social Capital and Sector Dynamics
Participants discussed a shared vision or shared agenda of what purpose data will serve and then the importance of making a plan. A key question they asked was: “What was the difference between rural and urban non-profits from an information sharing level?”
Participants highlighted the need to make common data available for all but recognized the struggle of overcoming privacy issues. Finally, taking a long-term perspective they discussed long term aggregate data and the importance of long term outcomes. These participants thought that data should be collected by a convening or governing organization.
5. Capacity
Participants reached a consensus that capacity remained a persistent challenge in working with data — including funding, and skillsets, but also that general knowledge negatively affected the other factors as well. There were several solutions and tactics identified by the group. Most participants agreed that the most basic tactics centred on sharing resources and skillsets — through collaborations, skilled volunteer recruitment, and creating funding for these specific skillsets. In addition, we also heard from participants that designing effective data infrastructure (e.g. standards and best practices) could also help alleviate the capacity problem by making data easier to work with. Lastly, most participants also expressed how it was important to build the capacity of the sector’s leadership to help spur more attention and investment from decision-makers.
Plenary Sector Discussion
At the end of the presentation, the whole group discussed our current situation regarding data – specifically answering what needs to stop, what needs to be improved, and what new things need to be created. Below are some of the ideas and submissions from participants:
What needs to stop?
- Reinventing the wheel
- Negative and territorial attitudes
- Excuses about why things haven’t changed
- Mistrust
- Not letting the citizens decide what they want to see
- Useless stuff
- Single year funding
- Saying we have to do everything and be perfectly ready before we have to go
- When data is analyzed or a report is created that there be no expectation for action
- Stop thinking planning and start doing
- Replicating data, point to the original
- Open washing
What needs to be improved or enhanced?
- Usability
- Processes (best practice, standard, sharing)
- Capacity
- Learning from our mistakes
- Networking
- Communications between different levels and reporting structures
- Responsibility for how data has been used or not used
- Indigenous data sovereignty
- Multisectoral ownership
- Success metrics
What sort of new things need to be created?
- Non-profit Data Strategies
- Metadata standards
Feedback on the Workshop
At the close of the workshop, participants were asked to complete a short survey to give their feedback on the session. About 55 participants responded to the survey. The following is a summary of their responses to various questions about the presentation.
Do you feel that the structure of the workshop allowed you to contribute your perspectives?
Most of the participants liked the combination of lecture and exercises and found the sessions engaging. They enjoyed the group discussion and felt the group worked well together. They indicated that the felt like it was a diverse group with varied skill levels which lead to fruitful discussions. This allowed some to mention the obstacles or their needs in terms of open data but also to feel understood. Moreover, this varied group allowed those without a background in the subject matter to still feel that their contributions were well received. Participants indicated that the small group discussions were particularly helpful and the structure offered lots of opportunity for discussion.
As for negatives, there was a complaint that room was not set up to hear all participants sharing their perspectives.
Was there an exercise or presentation that was particularly good at stimulating discussion and input from participants?
Among participants who filled out the survey, there was an overwhelming consensus that the most effective part of the workshop was the discussion and exercise about the 5 factors that influence the use and sharing of data. Participants particularly liked the exercise associated with this part because it allowed for information sharing and enhanced group discussion.
Other participants felt the first part of the presentation was most effective because it helped them conceptualize the material and the potential hurdles of open data.
Was there an exercise or presentation that was less effective in stimulating discussion or input from participants?
Most of the participants did not identify a less effective presentation. Some identified the early presentations as content heavy and too hard to understand. Among those who identified a less effective presentation, the majority clustered around the data continuum exercise on open, shared and closed data as less effective. For this exercise, they felt the goals and instructions were not clear and that the exercise did not generate much discussion from the group. Another cluster of participants identified the last exercise of the day as the least effective. Some indicated this may have been due to being tired after lunch and the long day. Others who echoed that this last exercise was the least effective mentioned it was redundant after the earlier 5 factors exercise. Instead they wanted to focus on finding solutions to overcoming obstacles.
What content or presentation sections did you find most valuable?
As for what content or presentation that was the most valuable, many participants felt the whole day was great and found all the content valuable. Some found the introductory presentation as the most valuable while others liked the data lifecycle framework or the data in nonprofit sector part that focused on leadership, policy, standards, technology, skills and resources. There was an appreciation for the Alberta perspective. However, similarly to the most effective presentation feedback, the 5 factors discussion and exercise came up as the most valuable by the most participants.
How would you restructure the workshop to be more effective?
The majority of respondents felt that nothing need to be re-structured. They thought the current structure was good because it encouraged folks to participate. Other suggestions to improve workshop ranged from more physical movement to keep folks awake to better communication about logistics like location and schedule.
Some thought that it was harder to focus on nonprofits due to the balance of stakeholders at each table and that perhaps different workshops for different folks on the learning curve about data would be helpful. They also thought that a better understanding of these different skill levels and an attunement to that would have proved fruitful.
Where some wanted denser and longer discussions others wanted a shorter workshop. There was as suggestion to share more material for people to read in advance in order to prepare for the discussions. The argument is that this would have led to more productive discussions and discussions more focused on action, problem solving and finding solutions.
In terms of format, participants thought it could include a panel Q & A with thought leaders in the sector or more case studies and success stories.
What content would you like to be added?
The largest cluster of responses indicated that nothing needed to be added. There were some suggestions from other respondents. Folks wanted more practical examples, information on available IT tools or open source software / databases, nonprofit government relations. Several participants wanted more information on data governance and how to do data privacy and protect sensitive data/marginalized
populations.
The biggest cluster of responses was the desire for more data success stories about open data in action and its benefits and impact end users. Others wanted more information data sharing and data collection activities with more concrete steps about the activities.
Conclusion
This report summarized the Data 4 Impact Workshop on June 12th, 2017 provided an overview of the workshop, a summary of the key discussions that took place during the workshop as well as a summary of the participant feedback in the post-conference survey. For further resources and information on the topics discussed in this report please see the following websites:
Appendix I – Results of Post-Workshop Survey
| Structure allowed you to contribute | Exercise or pres that was effective | Exercise or pres less effective | Content or pres most valuable | How to re-structure workshop more effective | Content – like to be added |
|---|---|---|---|---|---|
| – Yes | – Exercise discussing social capital, capacity, org culture, infrastructure – More opportunity to move groups would have been good (cover more than one topic | – Not really | – Discussions around current-state, potential resources | – More opportunity to work with others to capture concrete challenges and potential solutions | – Practical examples |
| – Yes, there were plenty of opportunity to contribute | – The exercise at the start (categorizing closed, shared, open data within our organizations to get the ball rolling | – No | – The activities were great | – Nothing | – Nothing |
| – Yes | – The breakout sessions – topics ere specific enough that allowed participants to select the topic that meant the most to them | – It was good – participants make a huge difference | – The introductory sessions | – I would almost want to see 2 workshops – 1 for the person who knew zip about open data and 1 for the person who was up the learning curve | – Really dumb it down for people like me |
| – Yes | – First discussion | – I was pretty tired after lunch | – Denser – towards the end the discussion got a bit long and wandered quite a bit | – How to do data privacy | |
| – Yes, I liked the balance of presentations & activity & collaborating | – Solutions tables were a great way to facilitate change thinking | – No | – The 5 stages and the activities around problem / solutions | – Food options did not take into consideration issues other than gluten & vegetarian. Dairy / wheat free would be appreciated | – Planning data collection activities, going through steps and viable options |
| – Yes, facilitated discussions allowed me to express my thoughts and concerns | – The part with closed, shared and open data sticky notes | ||||
| Yes, working in small groups and then broadening the scope of the discussions to include the whole group allowed for a sense of trust and allowed for more in-depth conversation | – Whole day stimulated valuable conversation | – Plenary discussion | – Shorter lunchtime – 30 to 45 minutes | ||
| – I like how the workshop was structured around the key themes or areas needed to support open data | – I was really interesting to hear about the Alberta non-profit data strategy. It would have been good to hear even more on this, | – To some extent it was difficult to focus on non-profits rather than public sector. Might have been better to make sure you had a balance of stakeholders at each table and help facilitate the inter sector conversations. | – Electronic surveys, snapchat, geofilter | ||
| – Yes | – Breakouts into 5 influencing factors | – At the end of the day, asking for participation from a tired room | – Breakout sections | – Shorter | – Talking about how the culture / world view of the data collectors and analyts create unintentionally biased data |
| – Yes | – Actually all were good. The best one may have been redundant | – Last one may have been redundant – or maybe everyone was just overly tired | – All were good | – I think I would have framed entire workshop around key questions to be answered leading all to last segment of agenda | – Policy and evidence-based decision making – Moving beyond open data to what its use will be |
| – Yes | Yes, 5 factors | – Available open data sources at various government levels | – Case studies, some success stories | – Available IT tools or open source software / databases | |
| – Yes | – Data Spectrum – 5 factors that influence data use and sharing | – No | – Data Spectrum and Data Lifecycle | – Current structure is good | – Data governance |
| – Yes, I like the interactive session where tables are shuffled. Good networking | – I like the mindset, capacity …. Discussion – It is good to see that there are potentially solutions to the problems we most of the time have in common | – No that I see – people are involved | – Your survey was interesting. Live survey is also very fun to do although technology hard to do | – Open data in action – cases where it is really beneficial – Data stories |
|
| – Yes | – Yes, the one in the afternoon | – First hour or so in the morning | – The content about mindset, org, etc. | – I would add an hour or so on the benefits (tangible) of open data | – Benefints, benefits, benefits … its then easy for government to get on-board |
| – It was well done – I like the mix of discussion and formal slides | – I enjoyed being able to move table to table | – The data lifecycle was valuable | – Keep it as is | ||
| – Definitely | – Group exercises were good – teams / tables wored well | – Data continuum exercise (notes on sheet of paper) | – Examples of existing initiatives – Maturity model | – More small exercises – Maybe a problem solving exercise | |
| – Yes | – The review of the various facets of open data; capacity, org, etc. | – No | – The perspectives of the other participants during the exercises | – Thought it was structured well – wouldn’t change anything except perhaps encouraging folks to use the mike when speaking | – Big vs. little orgs, their data and how big can better support little while having mutual trust |
| – Yes | – Discussion on the 5 barriers to open data | – Harder to find solutions to these 5 barriers | – The theory & princiles behind open data | – Not sure I saw what IMPACT open data has on end-users | |
| – Yes, it was a good flow of individual presentations with a mix of group work – More group work at the end of the day was better as it is harder to stay awake after lunch | – Breakout sessions to discuss how each of the 5 factors influence use and sharing of data | – Open, shared, closed data | – Discussion on the 5 factors | – Some questions and maybe seeing how people vote on them | |
| – Certainly | – Changing tables according to topics | – Sticky notes (somewhat) | – Listening to each tables’ summaries / conclusions | – Nothing, humour is great, maybe some videos | – Show concrete examples or tell us what organizations currently successfully share data |
| – Yes | – Suggestions; – make agenda available before – better communication about location, address was not in program | ||||
| – Yes | – The 1st & last one. The middle one | – The last plenary session felt repetitive | – The intro presentation | – Orient the agenda by goal and drive discussion to how the participants will use the info to take action | – Ask participants to identify 2-3 challenges & successes in their open data initiatives to use in discussion & brainstorm how to address |
| – Yes | – Exercise 2 was very engaging | – Lots of time to discuss exercise 2, maybe less next time | – Exercise 2 and the following discussion | – Maybe change up exercis 1 a litte more, another discussion would be better | – It was good |
| – Yes 100% | – I liked the 5 key factors exercise because it allowed us to critically think about what needs to be tackled | – No, all good | – The lifecycle framework of data | – I would add in an initial exercise to capture the existing understanding of open data to those who attended | – More information on maybe current data success stories / examples of HOW they did it |
| – Yes | – The solutions portion of the 5 factors that influence data | – The exercise on examples of closed/shared/ open data did not generate much discussion in my group | – Alberta perspective, specifically what exists, info available | – Mostly great, maybe add some physical movement mid-afternoon to wake us up | – More focus on sensitive data / marginalized populations |
| – Yes | – Talking solutions | – A bit more presentation on good practice / insights to promote data sharing – More detail on case studies and lessons learned | – How to deal with common issues with data sharing like getting consistent info and the ‘right’, ‘relevant’ info |
||
| – Yes, it was great | – The afternoon session with brainstorming the 5 factors that influence data collections | – No | |||
| – Absolutely | – The 1st part of the 2nd exercise, having numerous points to discuss helped stimulate peoples minds & bring forward different interests | – By the end people were communicating less on the different categories. Whether due to overlapping info or discussion or loss of focus | – As someone new to data concerns & developmental ideas I found it all very valuable | – I thought it was well done, timely, encouraged discussion, and thought provoking | |
| – Yes | – Small group discussion, afternoon format | – Panel Q&A with thought leaders in the sector | – Non-profit government relations – Data literacy |
||
| – Yes | – Whenever we drilled down on a particular idea | – Categorizing data into open, shared, closed | – Examples of effective projects and specific steps taken to make them happen | ||
| – Yes, and mingling between differenct groups allowed better perspective and sharing | – Open discussion on factors | – 2-minute discussion on things to stop, improve and create | – Factors were good holistic way to think about issues and opportunities | – Structure was good, no changes | – Content was appropriate to the topic |
| – Yes, it was a respectful and open environment | – The group discussion with a specific topic at the end (infrastructure for example) | – No | – The whole day | – I wouldn’t | – None |
| – Yes, liked combo of lecture and exercises | – Really liked groupwork on the 5 barriers | – Group I was with for morning exercise were not joiners | – 5 barriers / solutions | – Not content specific, but didn’t like logistics of workshop and conference in different places. Lots of people went to the wrong venue | |
| – Yes, it was quite engaging | – Table sessions on the Top 5 pillars of open data (culture, resources, etc.) | – New trends | – It was well done, good participation | – Value of open data, focus on storytelling and case studies, sharing best practices | |
| – Yes, the focus on group discussion followed by full room sharing worked well | – The group discussion on the 5 factors worked really well | – The group discussions | |||
| – Yes | Yes, first one after lunch discussing 5-factors | – Sticky notes on board, limited discussion after | – Nothing specific, was all fairly engaging and useful | ||
| – Yes | – I liked the two step dive into the 5 factors | – The last slide with the 3 sentences (stop, start, etc.) was hard to read, especially the last line with green on blue | – The data presentation wasn’t very useful. Also geospacial data was not discussed as a data type | – Would be good to have more about examples of impact from open data | – See last answer and ways to evaluate impact |
| – Yes, the small-group discussions helped, and I was fortunate to be at a table with a diverse group | – I liked the group discussions of the 5 factors | – I feel like more exploration could have been done on the Spectrum of Open Data. This may have helped to open up later discussion with respect to the 5 factors | |||
| – Yes, there was plenty of opportunity for discussion | – I think delving into the potential hurdles of open data was beneficial | – The last plenary discussion seemed almost superficial in comparison to the others | – Thank you for giving a section on Alberta data | – I would have loved a copy of the schedule for the day | – Honestly, this was less non-profit structured than I originally envisioned |
| – Yes | – Meeting new people and sharing experiences | – Better coffee | – More techy stuff, example how to normalize data, Excel best practices (non experts are curious, and can google/pursue a particular technology, but can easily get lost in the longo technically) | ||
| – Yes | – I liked discussing the issures and strategies to address | – Last one or maybe it was I was just tired by then | – Jesss’s and Geoff’s | – Maybe 1 hour shorter, I liked the 10am start | – Planning a datathon or collaboration event, where to start, key strategies |
| – Yes | – It was well facilitated | – No | – Not sure | – There were many differenct levels of competancy / capacity in the room around this topic, not sure we were all speaking the same language | – Data 101, using data to tell stories |
| – Yes, I had no background on the subject matter, but still felt my contributions were well received | – I liked them all but the first one really helped to conceptualize the material | – No | – All of the above, great introduction to data in nonprofit sector but also very valuable to have so many experts in the room | – A structured networking kind of activity – More on new areas to elaborate on |
|
| -Yes | – Specialized topics (digging into details) – The 5 factors | – List of data sets closed/shared/open more individual, not really discussed | – More on new areas to elaborate on | ||
| – Yes | – All discussions were pretty good | – Some audience questions / comments were not audible so I missed a few things | – The social capital part | – Not sure | – Not sure |
| – Yes | – The 5 dynamic conversations | – The 5 dynamics and next steps | – A chance for perspective sharing from differenct sectors | – Prototyping solutions | |
| – Yes | – Five factors that influence data use and sharing | – It was interesting to see all the sticky notes on the closed/shared/open poster, great ideas | – This was an interesting day and a learning experience, the workshop is effective as is | ||
| – Yes | – Didn’t feel as though I learned as much from the afternoon exercise | – Monitoring presentations | – Presentations on innovative use of open data | ||
| – Yes | – Both exercises were very informative, the open discussion and questions sessions | – No | – Both exercises being able to discuss the importance of data for all sectors | ||
| – Yes | – I liked the 5 factors and solutions table discussions | – Key components of Nonprofit Data Strategy including leadership, policy, standards, technology and skills / resources | – The workshop was well structured | ||
| – Yes, but room not set up well to hear all participants sharing | – 5 factor conversation | – What’s next | – Providing a tool box | – How to create capacity of organizations to evaluate and communicate their ‘why’ – Provide tools, how to collect, find and use data |
|
| – Yes, the workshop allowed everyone to contribute their obstacles, their needs in terms of open data as well as understand others perspectives | – Round table discussions about the 5 factors allowed information sharing and enhanced group discussion | – Since we did the round table discussion 5 factors, don’t see the need to spread out and do this discussion again. Rather focus on finding solutions to overcome these obstacles | – 5 factor discussion | – Add section on finding solutions | – Applying solutions / open data obstacles and solutions |
| – The session where we broke up by topic areas seemed to generate great conversations | – I felt the early presentations were content heavy and hard to understand | – Get a base understanding of where everyone is in terms of understanding firm issues | |||
| – Yes | – The 5 factors that affect data | – The spectrum of closed/shared/open was less effective, goal and instructions were not clear | – The table breakouts in the afternoon | – User stories, provide more context | |
| – Yes | – 5 factor discussion | – Initial presentation, examples of data initiatives worldwide | – Maybe some pre-work on 5 factors, articles / prep to support in advance | – Spectrum of data collections examples, ie. What are funders asking for, what data is collected in VIBRANT COMMUNITIES |